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MetaOmics: analysis pipeline and browser-based software suite for transcriptomic meta-analysis.
Ma, Tianzhou; Huo, Zhiguang; Kuo, Anche; Zhu, Li; Fang, Zhou; Zeng, Xiangrui; Lin, Chien-Wei; Liu, Silvia; Wang, Lin; Liu, Peng; Rahman, Tanbin; Chang, Lun-Ching; Kim, Sunghwan; Li, Jia; Park, Yongseok; Song, Chi; Oesterreich, Steffi; Sibille, Etienne; Tseng, George C.
Afiliación
  • Ma T; Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD, USA.
  • Huo Z; Department of Biostatistics, University of Florida, Gainesville, FL, USA.
  • Kuo A; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Zhu L; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Fang Z; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Zeng X; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Lin CW; Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI, USA.
  • Liu S; Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Wang L; School of Statistics, Capital University of Economics and Business, China.
  • Liu P; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Rahman T; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Chang LC; Department of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, USA.
  • Kim S; Department of Statistics, Keimyung University, Korea.
  • Li J; Henry Ford Health System, USA.
  • Park Y; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
  • Song C; Division of Biostatistics, Ohio State University, Columbus, OH, USA.
  • Oesterreich S; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Sibille E; Centre for Addiction and Mental Health, University of Toronto, Toronto, Canada.
  • Tseng GC; Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA, USA.
Bioinformatics ; 35(9): 1597-1599, 2019 05 01.
Article en En | MEDLINE | ID: mdl-30304367
ABSTRACT

SUMMARY:

The rapid advances of omics technologies have generated abundant genomic data in public repositories and effective analytical approaches are critical to fully decipher biological knowledge inside these data. Meta-analysis combines multiple studies of a related hypothesis to improve statistical power, accuracy and reproducibility beyond individual study analysis. To date, many transcriptomic meta-analysis methods have been developed, yet few thoughtful guidelines exist. Here, we introduce a comprehensive analytical pipeline and browser-based software suite, called MetaOmics, to meta-analyze multiple transcriptomic studies for various biological purposes, including quality control, differential expression analysis, pathway enrichment analysis, differential co-expression network analysis, prediction, clustering and dimension reduction. The pipeline includes many public as well as >10 in-house transcriptomic meta-analytic methods with data-driven and biological-aim-driven strategies, hands-on protocols, an intuitive user interface and step-by-step instructions. AVAILABILITY AND IMPLEMENTATION MetaOmics is freely available at https//github.com/metaOmics/metaOmics. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Transcriptoma Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Transcriptoma Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos